Plant phytochromes perceive red and far-red light to elicit adaptations to the changing environment. Downstream physiological responses revolve around red-light-induced interactions with phytochrome-interacting factors (PIF). Phytochromes double as thermoreceptors, owing to the pronounced temperature dependence of thermal reversion from the light-adapted Pfr to the dark-adapted Pr state. Here, we assess whether thermoreception may extend to the phytochrome:PIF interactions. While the association between Arabidopsis (Arabidopsis thaliana) PHYTOCHROME B (PhyB) and several PHYTOCHROME-INTERACTING FACTOR (PIF) variants moderately accelerates with temperature, the dissociation does more so, thus causing net destabilization of the phytochrome:PIF complex. Markedly different temperature profiles of PIF3 and PIF6 might underlie stratified temperature responses in plants. Accidentally, we identify a photoreception mechanism under strong continuous light, where the extent of phytochrome:PIF complexation decreases with red-light intensity rather than increases. Mathematical modeling rationalizes this attenuation mechanism and ties it to rapid red-light-driven Pr⇄Pfr interconversion and complex dissociation out of Pr. Varying phytochrome abundance, e.g., during diurnal and developmental cycles, and interaction dynamics, e.g., across different PIFs, modify the nature and extent of attenuation, thus permitting light-response profiles more malleable than possible for the phytochrome Pr⇄Pfr interconversion alone. Our data and analyses reveal a photoreception mechanism with implications for plant physiology, optogenetics, and biotechnological applications.

The use of prior knowledge in the machine learning framework has been considered a potential tool to handle the curse of dimensionality in genetic and genomics data. Although random forest (RF) represents a flexible non-parametric approach with several advantages, it can provide poor accuracy in high-dimensional settings, mainly in scenarios with small sample sizes. We propose a knowledge-slanted RF that integrates biological networks as prior knowledge into the model to improve its performance and explainability, exemplifying its use for selecting and identifying relevant genes. knowledge-slanted RF is a combination of two stages. First, prior knowledge represented by graphs is translated by running a random walk with restart algorithm to determine the relevance of each gene based on its connection and localization on a protein-protein interaction network. Then, each relevance is used to modify the selection probability to draw a gene as a candidate split-feature in the conventional RF. Experiments in simulated datasets with very small sample sizes ( n ≤ 30 ) comparing knowledge-slanted RF against conventional RF and logistic lasso regression, suggest an improved precision in outcome prediction compared to the other methods. The knowledge-slanted RF was completed with the introduction of a modified version of the Boruta feature selection algorithm. Finally, knowledge-slanted RF identified more relevant biological genes, offering a higher level of explainability for users than conventional RF. These findings were corroborated in one real case to identify relevant genes to calcific aortic valve stenosis.

Colon cancer is a significant public health issue, and a deeper understanding of the molecular fundamentals [16] ehind is required to improve sensitivity and curability. This research explored the gene NDUFAF4 as a target of concern due to its link to a mitochondrial function and protein \"Relatively of liver tumorigenesis\", which remains unclear is attributable to its inclusion into the complex I (CI) pathway. The gene ontology analysis, in turn, showed that NDUFAF4 is a key player in several critical biological phases linked to mitochondrial function and energy metabolism. Furthermore, survival analysis displayed that there was a strong correlation between NDUFAF4 expression and the patients\' longevity suggesting that this factor may be important in colon cancer prognosis as well. The TCGA data proved that NDUFAF4 is elevated in colon cancer making the results of the analysis reported credible. All of the above justified the understanding of the role and importance of NDUFAF4 in treating each colon cancer patient as a molecular target. The findings help in understanding the colon cancer pathogenesis and suggest ways for developing more efficient diagnosis and treatment of the disease. SIGNIFICANCE: This research explored the gene NDUFAF4 as a target of concern due to its link to a mitochondrial function and protein \"Relatively of liver tumorigenesis\", which remains unclear is attributable to its inclusion into the complex I (CI) pathway. Using a comprehensive approach to Gene Ontology analysis, Protein-Protein Interaction network modelling, survival analysis, KEGG pathway analysis, and validation using TCGA data, we identified the activities of NDUFAF4 in colon cancer. The Gene Ontology analysis, in turn, showed that NDUFAF4 is a key player in several critical biological phases linked to mitochondrial function and energy metabolism. The construction of the PPI network illustrates the interactors of NDUFAF4, the functional association protein within the cellular regulatory networks. In addition, survival analysis indicated that there was a considerable relationship between the expression of NDUFAF4 and patient survival, indicating its potential role as a prognostic factor in colon cancer. KEGG pathway analysis suggested that NDUFAF4 plays a role in thermogenesis and mitochondrial biogenesis, biological processes that should be targeted due to their implication in cellular metabolism and cancer onset. The use of TCGA information confirmed the upregulation of NDUFAF4 in colon cancer, thus making the findings of the analysis reported dependable. Overall, our study provided necessary information on the role and significance of NDUFAF4, a potential molecular target in colon cancer cases. These present findings enhance our knowledge of the pathogenesis of colon cancer and open new opportunities for designing novel diagnostic and therapeutic approaches to improve patient outcomes.

Coronavirus nonstructural protein 2 (Nsp2) is regarded as a virulence determinant and plays a critical role in virus replication, and innate immunity. Screening and identifying host cell proteins that interact with viral proteins is an effective way to reveal the functions of viral proteins. In this study, the host proteins that interacted with transmissible gastroenteritis virus (TGEV) Nsp2 were identified using immunoprecipitation combined with LC-MS/MS. 77 host cell proteins were identified as putative Nsp2 interaction host cell proteins and a protein-protein interaction (PPI) was constructed. The identified proteins were found to be associated with various subcellular locations and functional categories through Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. It is hypothesized that the host cell proteins interacting with TGEV Nsp2 are mainly involved in the formation of the cytoplasmic translation initiation complex, mRNA binding, ribosomes, and proteasomes. Among these, the ATP5B, a core subunit of the mitochondrial ATP synthase was further studied. The Coimmunoprecipitation (Co-IP) and indirect immunofluorescence (IFA) results confirmed that TGEV Nsp2 interacted with ATP5B. Furthermore, the downregulation of ATP5B expression was found to promote TGEV replication, suggesting that ATP5B might function as a negative regulator of TGEV replication. Collectively, our results offer additional insights into the functions of Nsp2 and provide a novel antiviral target against TGEV.

OBJECTIVE: Signal transducer and activator of transcription 3 (STAT3) is one of the key proliferation mechanism-related proteins that helps in oral squamous cell carcinoma (OSCC) progression. Immune evasion by STAT3 is mediated by the JAK2/STAT3/PDL1 signaling axis. Based on previous findings, we hypothesized that STAT3-binding partners participate in the inhibition of anti-tumor activity in OSCC.
METHODS: A 3D cancer-immune co-culture model was constructed using oral cancer cell lines SCC4, SCC9, SCC25, and CAL27 and normal oral cell line OKF6. The cells were co-cultured with natural killer (NK-92) and Jurkat cells. The target protein STAT3 was chosen based on SWATH data, and co-immunoprecipitation (Co-IP)-based proteomics was conducted. The Co-IP LC-MS/MS output was analyzed to determine the protein interaction network, gene ontology, pathway analysis, and protein cluster annotation.
RESULTS: STAT3 in oral cancer cell lines interacts with the epidermal growth factor receptor (EGFR) and other proteins that participate in proliferation and immune mechanisms. Proteome analysis showed that some STAT3-binding proteins found in this study are known immune system regulators.
CONCLUSIONS: Overall, STAT3 interactive proteins regulate the immune system in oral squamous cell carcinoma cells.

Introduction: Esophageal squamous cell carcinoma (ESCC) accounts for over 90% of all esophageal tumors. However, the molecular mechanism underlying ESCC development and prognosis remains unclear, and there are still no effective molecular biomarkers for diagnosing or predicting the clinical outcome of patients with ESCC. Here, we used bioinformatics analysis to identify potential biomarkers and therapeutic targets for ESCC. Methodology: Differentially expressed genes (DEGs) between ESCC and normal esophageal tissue samples were obtained by comprehensively analyzing publicly available RNA-seq datasets from the TCGA and GTEX. Gene Ontology (GO) annotation and Reactome pathway analysis identified the biological roles of the DEGs. Moreover, the Cytoscape 3.10.1 platform and subsidiary tools such as CytoHubba were used to visualize the DEGs\' protein-protein interaction (PPI) network and identify hub genes, Furthermore our results are validated by using Single-cell RNA analysis. Results: Identification of 2524 genes exhibiting altered expression enriched in pathways including keratinization, epidermal cell differentiation, G alpha(s) signaling events, and biological process of cell proliferation and division, extracellular matrix (ECM) disassembly, and muscle function. Moreover, upregulation of hallmarks E2F targets, G2M checkpoints, and TNF signaling. CytoHubba revealed 20 hub genes that had a valuable influence on the progression of ESCC in these patients. Among these, the high expression levels of four genes, CDK1 MAD2L1, PLK1, and TOP2A, were associated with critical dependence for cell survival in ESCC cell lines, as indicated by CRISPR dependency scores, gene expression data, and cell line metadata. We also identify the molecules targeting these essential hub genes, among which GSK461364 is a promising inhibitor of PLK1, BMS265246, and Valrubicin inhibitors of CDK1 and TOP2A, respectively. Moreover, we identified that elevated expression of MMP9 is associated with worse overall survival in ESCC patients, which may serve as potential prognostic biomarker or therapeutic target for ESCC. The single-cell RNA analysis showed MMP9 is highly expressed in myeloid, fibroblast, and epithelial cells, but low in T cells, endothelial cells, and B cells. This suggests MMP9\'s role in tumor progression and matrix remodeling, highlighting its potential as a prognostic marker and therapeutic target. Discussion: Our study identified key hub genes in ESCC, assessing their potential as therapeutic targets and biomarkers through detailed expression and dependency analyses. Notably, MMP9 emerged as a significant prognostic marker with high expression correlating with poor survival, underscoring its potential for targeted therapy. These findings enhance our understanding of ESCC pathogenesis and highlight promising avenues for treatment.

Gas vesicles (GVs) are gas-filled microbial organelles formed by unique 3-nm thick, amphipathic, force-bearing protein shells, which can withstand multiple atmospheric pressures and maintain a physically stable air bubble with megapascal surface tension. However, the molecular process of GV assembly remains elusive. To begin understanding this process, we have devised a high-throughput in vivo assay to determine the interactions of all 11 proteins in the pNL29 GV operon. Complete or partial deletions of the operon establish interdependent relationships among GV proteins during assembly. We also examine the tolerance of the GV assembly process to protein mutations and the cellular burdens caused by GV proteins. Clusters of GV protein interactions are revealed, proposing plausible protein complexes that are important for GV assembly. We anticipate our findings will set the stage for designing GVs that efficiently assemble in heterologous hosts during biomedical applications.

Mitochondrial fusion requires the sequential merger of four bilayers to two. The outer-membrane solute carrier protein SLC25A46 interacts with both the outer and inner-membrane dynamin family GTPases Mfn1/2 and Opa1. While SLC25A46 levels are known to affect mitochondrial morphology, how SLC25A46 interacts with Mfn1/2 and Opa1 to regulate membrane fusion is not understood. In this study, we use crosslinking mass-spectrometry and AlphaFold 2 modeling to identify interfaces mediating a SLC25A46 interactions with Opa1 and Mfn2. We reveal that the bundle signaling element of Opa1 interacts with SLC25A46, and present evidence of a Mfn2 interaction involving the SLC25A46 cytosolic face. We validate these newly identified interaction interfaces and show that they play a role in mitochondrial network maintenance.

Ubiquitin-specific proteases (USPs) are a family of multi-domain deubiquitinases (DUBs) with variable architectures, some containing regulatory auxiliary domains. Among the USP family, all occurrences of intramolecular regulation presently known are autoactivating. USP8 remains the sole exception as its putative WW-like domain, conserved only in vertebrate orthologs, is autoinhibitory. Here, we present a comprehensive structure-function analysis describing the autoinhibition of USP8 and provide evidence of the physical interaction between the WW-like and catalytic domains. The solution structure of full-length USP8 reveals an extended, monomeric conformation. Coupled with DUB assays, the WW-like domain is confirmed to be the minimal autoinhibitory unit. Strikingly, autoinhibition is only observed with the WW-like domain in cis and depends on the length of the linker tethering it to the catalytic domain. Modelling of the WW:CD complex structure and mutagenesis of interface residues suggests a novel binding site in the S1 pocket. To investigate the interplay between phosphorylation and USP8 autoinhibition, we identify AMP-activated protein kinase as a highly selective modifier of S718 in the 14-3-3 binding motif. We show that 14-3-3γ binding to phosphorylated USP8 potentiates autoinhibition in a WW-like domain-dependent manner by stabilizing an autoinhibited conformation. These findings provide mechanistic details on the autoregulation of USP8 and shed light on its evolutionary significance.

Mutations of human TBC1D24 are associated with either deafness, epilepsy or DOORS syndrome (deafness, onychodystrophy, osteodystrophy, cognitive disability, seizures). The causal relationships between TBC1D24 variants and the different clinical phenotypes are not understood. Our hypothesis is that phenotypic heterogeneity of missense mutations of TBC1D24 results, in part, from perturbed binding of different protein partners. To discover novel protein partners of TBC1D24, we conducted a yeast two-hybrid (Y2H) screen using mouse full-length (FL) TBC1D24 as bait. KIBRA, a scaffold protein encoded by Wwc1, was identified as a partner of TBC1D24. KIBRA functions in the Hippo signaling pathway and is important for human cognition and memory. The TBC1D24 TLDc domain binds to KIBRA FL and to its C2 domain, confirmed by Y2H assays. No interaction was detected with Y2H assays between the KIBRA C2 domain and TLDc domains of NCOA7, MEAK7 and OXR1. Moreover, the C2 domains of other WWC family proteins do not interact with the TLDc domain of TBC1D24, demonstrating specificity. The mRNAs encoding TBC1D24 and KIBRA proteins in mouse are coexpressed at least in a subset of hippocampal cells indicating availability to interact in vivo. As two epilepsy-associated recessive variants (Gly511Arg and Ala515Val) in the TLDc domain of human TBC1D24 disrupt the interaction with human KIBRA C2 domain, this study reveals a pathogenic mechanism of TBC1D24-associated epilepsy, linking the TBC1D24 and KIBRA pathways. The interaction of TBC1D24-KIBRA is physiologically meaningful and necessary to reduce the risk of epilepsy.